Overview

Dataset statistics

Number of variables28
Number of observations86
Missing cells34
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.9 KiB
Average record size in memory225.5 B

Variable types

Numeric9
Categorical19

Alerts

airdate has constant value "2020-12-23" Constant
url has a high cardinality: 86 distinct values High cardinality
name has a high cardinality: 74 distinct values High cardinality
_embedded_show_url has a high cardinality: 62 distinct values High cardinality
_embedded_show_name has a high cardinality: 62 distinct values High cardinality
_embedded_show_premiered has a high cardinality: 53 distinct values High cardinality
_embedded_show_officialSite has a high cardinality: 54 distinct values High cardinality
_embedded_show_summary has a high cardinality: 54 distinct values High cardinality
_links_self_href has a high cardinality: 86 distinct values High cardinality
season is highly correlated with _embedded_show_updatedHigh correlation
number is highly correlated with _embedded_show_runtimeHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with number and 2 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_updated is highly correlated with seasonHigh correlation
season is highly correlated with number and 2 other fieldsHigh correlation
number is highly correlated with season and 2 other fieldsHigh correlation
runtime is highly correlated with season and 3 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with season and 3 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with summary and 15 other fieldsHigh correlation
summary is highly correlated with _embedded_show_officialSite and 9 other fieldsHigh correlation
_embedded_show_summary is highly correlated with _embedded_show_officialSite and 13 other fieldsHigh correlation
_embedded_show_type is highly correlated with _embedded_show_officialSite and 7 other fieldsHigh correlation
_embedded_show_status is highly correlated with _embedded_show_officialSite and 10 other fieldsHigh correlation
url is highly correlated with _embedded_show_officialSite and 17 other fieldsHigh correlation
_embedded_show_ended is highly correlated with _embedded_show_summary and 6 other fieldsHigh correlation
_embedded_show_name is highly correlated with _embedded_show_officialSite and 16 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with _embedded_show_officialSite and 15 other fieldsHigh correlation
name is highly correlated with url and 2 other fieldsHigh correlation
airdate is highly correlated with _embedded_show_officialSite and 17 other fieldsHigh correlation
airtime is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
_links_self_href is highly correlated with _embedded_show_officialSite and 17 other fieldsHigh correlation
_embedded_show_genres is highly correlated with _embedded_show_officialSite and 9 other fieldsHigh correlation
type is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
_embedded_show_url is highly correlated with _embedded_show_officialSite and 16 other fieldsHigh correlation
_embedded_show_language is highly correlated with _embedded_show_officialSite and 8 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with _embedded_show_officialSite and 9 other fieldsHigh correlation
airstamp is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
id is highly correlated with url and 12 other fieldsHigh correlation
url is highly correlated with id and 25 other fieldsHigh correlation
name is highly correlated with id and 23 other fieldsHigh correlation
season is highly correlated with url and 13 other fieldsHigh correlation
number is highly correlated with url and 14 other fieldsHigh correlation
type is highly correlated with url and 12 other fieldsHigh correlation
airtime is highly correlated with url and 19 other fieldsHigh correlation
airstamp is highly correlated with url and 22 other fieldsHigh correlation
runtime is highly correlated with url and 20 other fieldsHigh correlation
summary is highly correlated with url and 14 other fieldsHigh correlation
_embedded_show_id is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_url is highly correlated with id and 25 other fieldsHigh correlation
_embedded_show_name is highly correlated with id and 25 other fieldsHigh correlation
_embedded_show_type is highly correlated with url and 19 other fieldsHigh correlation
_embedded_show_language is highly correlated with id and 20 other fieldsHigh correlation
_embedded_show_genres is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_status is highly correlated with url and 17 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with url and 21 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with url and 21 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with id and 25 other fieldsHigh correlation
_embedded_show_ended is highly correlated with id and 17 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with id and 25 other fieldsHigh correlation
_embedded_show_weight is highly correlated with url and 18 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with url and 14 other fieldsHigh correlation
_embedded_show_summary is highly correlated with id and 24 other fieldsHigh correlation
_embedded_show_updated is highly correlated with id and 17 other fieldsHigh correlation
_links_self_href is highly correlated with id and 25 other fieldsHigh correlation
number has 4 (4.7%) missing values Missing
runtime has 7 (8.1%) missing values Missing
_embedded_show_runtime has 18 (20.9%) missing values Missing
_embedded_show_averageRuntime has 5 (5.8%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
_links_self_href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links_self_href has unique values Unique

Reproduction

Analysis started2022-05-10 02:19:18.041184
Analysis finished2022-05-10 02:19:48.938590
Duration30.9 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct86
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2034158.558
Minimum1945147
Maximum2318111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-05-09T21:19:49.009588image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1945147
5-th percentile1965935.5
Q11987998.5
median1997667
Q32068318.75
95-th percentile2196123.25
Maximum2318111
Range372964
Interquartile range (IQR)80320.25

Descriptive statistics

Standard deviation75115.80656
Coefficient of variation (CV)0.0369272131
Kurtosis1.900745042
Mean2034158.558
Median Absolute Deviation (MAD)19161.5
Skewness1.537188198
Sum174937636
Variance5642384395
MonotonicityNot monotonic
2022-05-09T21:19:49.115075image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21796141
 
1.2%
19776501
 
1.2%
19880681
 
1.2%
19963971
 
1.2%
19854761
 
1.2%
19854751
 
1.2%
19849571
 
1.2%
19849561
 
1.2%
21296331
 
1.2%
19776511
 
1.2%
Other values (76)76
88.4%
ValueCountFrequency (%)
19451471
1.2%
19459021
1.2%
19585751
1.2%
19588681
1.2%
19644961
1.2%
19702541
1.2%
19760461
1.2%
19760471
1.2%
19773311
1.2%
19774181
1.2%
ValueCountFrequency (%)
23181111
1.2%
22059791
1.2%
22059781
1.2%
21975981
1.2%
21972891
1.2%
21926261
1.2%
21796141
1.2%
21761401
1.2%
21661961
1.2%
21560151
1.2%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct86
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size816.0 B
https://www.tvmaze.com/episodes/2179614/kontakty-1x31-kontakty-v-telefone-eldara-dzarahova-morgenshtern-slava-marlow-basta-dana-poperecnyj
 
1
https://www.tvmaze.com/episodes/1977650/to-love-1x39-episode-39
 
1
https://www.tvmaze.com/episodes/1988068/forever-love-1x17-episode-17
 
1
https://www.tvmaze.com/episodes/1996397/the-expanse-aftershow-1x04-shohreh-aghdashloo-dan-nowak
 
1
https://www.tvmaze.com/episodes/1985476/you-complete-me-1x20-episode-20
 
1
Other values (81)
81 

Length

Max length138
Median length102
Mean length79.44186047
Min length63

Characters and Unicode

Total characters6832
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2179614/kontakty-1x31-kontakty-v-telefone-eldara-dzarahova-morgenshtern-slava-marlow-basta-dana-poperecnyj
2nd rowhttps://www.tvmaze.com/episodes/1988015/muzskaa-tema-1x04-seria-4
3rd rowhttps://www.tvmaze.com/episodes/2095629/yi-nian-yong-heng-1x22-episode-22
4th rowhttps://www.tvmaze.com/episodes/1993657/7-days-of-romance-2x02-episode-2
5th rowhttps://www.tvmaze.com/episodes/2015712/half-fifty-1x01-episode-1

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2179614/kontakty-1x31-kontakty-v-telefone-eldara-dzarahova-morgenshtern-slava-marlow-basta-dana-poperecnyj1
 
1.2%
https://www.tvmaze.com/episodes/1977650/to-love-1x39-episode-391
 
1.2%
https://www.tvmaze.com/episodes/1988068/forever-love-1x17-episode-171
 
1.2%
https://www.tvmaze.com/episodes/1996397/the-expanse-aftershow-1x04-shohreh-aghdashloo-dan-nowak1
 
1.2%
https://www.tvmaze.com/episodes/1985476/you-complete-me-1x20-episode-201
 
1.2%
https://www.tvmaze.com/episodes/1985475/you-complete-me-1x19-episode-191
 
1.2%
https://www.tvmaze.com/episodes/1984957/dream-detective-1x18-episode-181
 
1.2%
https://www.tvmaze.com/episodes/1984956/dream-detective-1x17-episode-171
 
1.2%
https://www.tvmaze.com/episodes/2129633/the-aam-aadmi-family-4x02-mard-ko-dard-nahi-hota1
 
1.2%
https://www.tvmaze.com/episodes/1977651/to-love-1x40-episode-401
 
1.2%
Other values (76)76
88.4%

Length

2022-05-09T21:19:49.242208image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2179614/kontakty-1x31-kontakty-v-telefone-eldara-dzarahova-morgenshtern-slava-marlow-basta-dana-poperecnyj1
 
1.2%
https://www.tvmaze.com/episodes/2015718/half-fifty-1x07-episode-71
 
1.2%
https://www.tvmaze.com/episodes/1993657/7-days-of-romance-2x02-episode-21
 
1.2%
https://www.tvmaze.com/episodes/2015712/half-fifty-1x01-episode-11
 
1.2%
https://www.tvmaze.com/episodes/2015713/half-fifty-1x02-episode-21
 
1.2%
https://www.tvmaze.com/episodes/2015714/half-fifty-1x03-episode-31
 
1.2%
https://www.tvmaze.com/episodes/2015715/half-fifty-1x04-episode-41
 
1.2%
https://www.tvmaze.com/episodes/2015716/half-fifty-1x05-episode-51
 
1.2%
https://www.tvmaze.com/episodes/2015717/half-fifty-1x06-episode-61
 
1.2%
https://www.tvmaze.com/episodes/2041158/dtk-elviszlek-magammal-7x20-bach-kata-es-wunderlich-jozsef1
 
1.2%
Other values (76)76
88.4%

Most occurring characters

ValueCountFrequency (%)
e588
 
8.6%
-523
 
7.7%
s433
 
6.3%
/430
 
6.3%
t407
 
6.0%
o351
 
5.1%
a307
 
4.5%
w284
 
4.2%
i250
 
3.7%
p247
 
3.6%
Other values (30)3012
44.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4620
67.6%
Decimal Number1001
 
14.7%
Other Punctuation688
 
10.1%
Dash Punctuation523
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e588
12.7%
s433
 
9.4%
t407
 
8.8%
o351
 
7.6%
a307
 
6.6%
w284
 
6.1%
i250
 
5.4%
p247
 
5.3%
m246
 
5.3%
d199
 
4.3%
Other values (16)1308
28.3%
Decimal Number
ValueCountFrequency (%)
1220
22.0%
0156
15.6%
2149
14.9%
999
9.9%
768
 
6.8%
866
 
6.6%
564
 
6.4%
363
 
6.3%
658
 
5.8%
458
 
5.8%
Other Punctuation
ValueCountFrequency (%)
/430
62.5%
.172
 
25.0%
:86
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-523
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4620
67.6%
Common2212
32.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e588
12.7%
s433
 
9.4%
t407
 
8.8%
o351
 
7.6%
a307
 
6.6%
w284
 
6.1%
i250
 
5.4%
p247
 
5.3%
m246
 
5.3%
d199
 
4.3%
Other values (16)1308
28.3%
Common
ValueCountFrequency (%)
-523
23.6%
/430
19.4%
1220
9.9%
.172
 
7.8%
0156
 
7.1%
2149
 
6.7%
999
 
4.5%
:86
 
3.9%
768
 
3.1%
866
 
3.0%
Other values (4)243
11.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6832
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e588
 
8.6%
-523
 
7.7%
s433
 
6.3%
/430
 
6.3%
t407
 
6.0%
o351
 
5.1%
a307
 
4.5%
w284
 
4.2%
i250
 
3.7%
p247
 
3.6%
Other values (30)3012
44.1%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct74
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size816.0 B
Episode 18
 
3
Episode 17
 
3
Episode 22
 
2
Episode 2
 
2
Episode 1
 
2
Other values (69)
74 

Length

Max length89
Median length67
Mean length17.91860465
Min length1

Characters and Unicode

Total characters1541
Distinct characters156
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)74.4%

Sample

1st rowКОНТАКТЫ в телефоне Эльдара Джарахова: Morgenshtern, Slava Marlow, Баста, Даня Поперечный
2nd rowСерия 4
3rd rowEpisode 22
4th rowEpisode 2
5th rowEpisode 1

Common Values

ValueCountFrequency (%)
Episode 183
 
3.5%
Episode 173
 
3.5%
Episode 222
 
2.3%
Episode 22
 
2.3%
Episode 12
 
2.3%
Episode 32
 
2.3%
Episode 42
 
2.3%
Christmas Special2
 
2.3%
Episode 72
 
2.3%
Episode 82
 
2.3%
Other values (64)64
74.4%

Length

2022-05-09T21:19:49.399700image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode34
 
12.1%
the8
 
2.9%
26
 
2.1%
6
 
2.1%
15
 
1.8%
of4
 
1.4%
christmas4
 
1.4%
be3
 
1.1%
희대의3
 
1.1%
183
 
1.1%
Other values (180)204
72.9%

Most occurring characters

ValueCountFrequency (%)
194
 
12.6%
e102
 
6.6%
o75
 
4.9%
i68
 
4.4%
s63
 
4.1%
a58
 
3.8%
d52
 
3.4%
p40
 
2.6%
r39
 
2.5%
E38
 
2.5%
Other values (146)812
52.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter948
61.5%
Uppercase Letter217
 
14.1%
Space Separator194
 
12.6%
Decimal Number91
 
5.9%
Other Letter49
 
3.2%
Other Punctuation28
 
1.8%
Dash Punctuation5
 
0.3%
Close Punctuation4
 
0.3%
Open Punctuation4
 
0.3%
Math Symbol1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e102
 
10.8%
o75
 
7.9%
i68
 
7.2%
s63
 
6.6%
a58
 
6.1%
d52
 
5.5%
p40
 
4.2%
r39
 
4.1%
t37
 
3.9%
n37
 
3.9%
Other values (47)377
39.8%
Uppercase Letter
ValueCountFrequency (%)
E38
 
17.5%
S13
 
6.0%
К11
 
5.1%
T10
 
4.6%
D9
 
4.1%
C8
 
3.7%
M8
 
3.7%
А7
 
3.2%
B7
 
3.2%
С6
 
2.8%
Other values (36)100
46.1%
Other Letter
ValueCountFrequency (%)
7
 
14.3%
3
 
6.1%
3
 
6.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
Other values (21)22
44.9%
Decimal Number
ValueCountFrequency (%)
227
29.7%
116
17.6%
010
 
11.0%
310
 
11.0%
86
 
6.6%
75
 
5.5%
55
 
5.5%
65
 
5.5%
44
 
4.4%
93
 
3.3%
Other Punctuation
ValueCountFrequency (%)
,15
53.6%
:3
 
10.7%
'3
 
10.7%
.2
 
7.1%
/2
 
7.1%
&2
 
7.1%
?1
 
3.6%
Space Separator
ValueCountFrequency (%)
194
100.0%
Dash Punctuation
ValueCountFrequency (%)
-5
100.0%
Close Punctuation
ValueCountFrequency (%)
)4
100.0%
Open Punctuation
ValueCountFrequency (%)
(4
100.0%
Math Symbol
ValueCountFrequency (%)
|1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin875
56.8%
Common327
 
21.2%
Cyrillic290
 
18.8%
Hangul49
 
3.2%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
а34
 
11.7%
е20
 
6.9%
р18
 
6.2%
н15
 
5.2%
о12
 
4.1%
с11
 
3.8%
и11
 
3.8%
К11
 
3.8%
т10
 
3.4%
к9
 
3.1%
Other values (44)139
47.9%
Latin
ValueCountFrequency (%)
e102
 
11.7%
o75
 
8.6%
i68
 
7.8%
s63
 
7.2%
a58
 
6.6%
d52
 
5.9%
p40
 
4.6%
r39
 
4.5%
E38
 
4.3%
t37
 
4.2%
Other values (39)303
34.6%
Hangul
ValueCountFrequency (%)
7
 
14.3%
3
 
6.1%
3
 
6.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
Other values (21)22
44.9%
Common
ValueCountFrequency (%)
194
59.3%
227
 
8.3%
116
 
4.9%
,15
 
4.6%
010
 
3.1%
310
 
3.1%
86
 
1.8%
75
 
1.5%
55
 
1.5%
65
 
1.5%
Other values (12)34
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1199
77.8%
Cyrillic290
 
18.8%
Hangul49
 
3.2%
None3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
194
16.2%
e102
 
8.5%
o75
 
6.3%
i68
 
5.7%
s63
 
5.3%
a58
 
4.8%
d52
 
4.3%
p40
 
3.3%
r39
 
3.3%
E38
 
3.2%
Other values (58)470
39.2%
Cyrillic
ValueCountFrequency (%)
а34
 
11.7%
е20
 
6.9%
р18
 
6.2%
н15
 
5.2%
о12
 
4.1%
с11
 
3.8%
и11
 
3.8%
К11
 
3.8%
т10
 
3.4%
к9
 
3.1%
Other values (44)139
47.9%
Hangul
ValueCountFrequency (%)
7
 
14.3%
3
 
6.1%
3
 
6.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
Other values (21)22
44.9%
None
ValueCountFrequency (%)
å1
33.3%
é1
33.3%
ó1
33.3%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.40697674
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-05-09T21:19:49.486307image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile27.75
Maximum2020
Range2019
Interquartile range (IQR)2

Descriptive statistics

Standard deviation427.3621794
Coefficient of variation (CV)4.432896808
Kurtosis17.62215985
Mean96.40697674
Median Absolute Deviation (MAD)0
Skewness4.382996912
Sum8291
Variance182638.4324
MonotonicityNot monotonic
2022-05-09T21:19:49.576767image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
156
65.1%
48
 
9.3%
26
 
7.0%
20204
 
4.7%
73
 
3.5%
33
 
3.5%
52
 
2.3%
81
 
1.2%
181
 
1.2%
311
 
1.2%
ValueCountFrequency (%)
156
65.1%
26
 
7.0%
33
 
3.5%
48
 
9.3%
52
 
2.3%
73
 
3.5%
81
 
1.2%
141
 
1.2%
181
 
1.2%
311
 
1.2%
ValueCountFrequency (%)
20204
4.7%
311
 
1.2%
181
 
1.2%
141
 
1.2%
81
 
1.2%
73
 
3.5%
52
 
2.3%
48
9.3%
33
 
3.5%
26
7.0%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct39
Distinct (%)47.6%
Missing4
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean28.8902439
Minimum1
Maximum350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-05-09T21:19:49.695065image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8.5
Q322.75
95-th percentile85.3
Maximum350
Range349
Interquartile range (IQR)18.75

Descriptive statistics

Standard deviation61.93405615
Coefficient of variation (CV)2.143770622
Kurtosis18.73259632
Mean28.8902439
Median Absolute Deviation (MAD)6.5
Skewness4.269574088
Sum2369
Variance3835.827311
MonotonicityNot monotonic
2022-05-09T21:19:49.795435image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
48
 
9.3%
27
 
8.1%
16
 
7.0%
35
 
5.8%
65
 
5.8%
75
 
5.8%
83
 
3.5%
183
 
3.5%
173
 
3.5%
203
 
3.5%
Other values (29)34
39.5%
(Missing)4
 
4.7%
ValueCountFrequency (%)
16
7.0%
27
8.1%
35
5.8%
48
9.3%
52
 
2.3%
65
5.8%
75
5.8%
83
 
3.5%
91
 
1.2%
102
 
2.3%
ValueCountFrequency (%)
3501
1.2%
3161
1.2%
3151
1.2%
901
1.2%
861
1.2%
721
1.2%
671
1.2%
611
1.2%
581
1.2%
551
1.2%

type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size816.0 B
regular
82 
significant_special
 
4

Length

Max length19
Median length7
Mean length7.558139535
Min length7

Characters and Unicode

Total characters650
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular82
95.3%
significant_special4
 
4.7%

Length

2022-05-09T21:19:49.903025image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:19:49.997570image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
regular82
95.3%
significant_special4
 
4.7%

Most occurring characters

ValueCountFrequency (%)
r164
25.2%
a90
13.8%
e86
13.2%
g86
13.2%
l86
13.2%
u82
12.6%
i16
 
2.5%
s8
 
1.2%
n8
 
1.2%
c8
 
1.2%
Other values (4)16
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter646
99.4%
Connector Punctuation4
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r164
25.4%
a90
13.9%
e86
13.3%
g86
13.3%
l86
13.3%
u82
12.7%
i16
 
2.5%
s8
 
1.2%
n8
 
1.2%
c8
 
1.2%
Other values (3)12
 
1.9%
Connector Punctuation
ValueCountFrequency (%)
_4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin646
99.4%
Common4
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r164
25.4%
a90
13.9%
e86
13.3%
g86
13.3%
l86
13.3%
u82
12.7%
i16
 
2.5%
s8
 
1.2%
n8
 
1.2%
c8
 
1.2%
Other values (3)12
 
1.9%
Common
ValueCountFrequency (%)
_4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII650
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r164
25.2%
a90
13.8%
e86
13.2%
g86
13.2%
l86
13.2%
u82
12.6%
i16
 
2.5%
s8
 
1.2%
n8
 
1.2%
c8
 
1.2%
Other values (4)16
 
2.5%

airdate
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size816.0 B
2020-12-23
86 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters860
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-23
2nd row2020-12-23
3rd row2020-12-23
4th row2020-12-23
5th row2020-12-23

Common Values

ValueCountFrequency (%)
2020-12-2386
100.0%

Length

2022-05-09T21:19:50.091912image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:19:50.170889image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-2386
100.0%

Most occurring characters

ValueCountFrequency (%)
2344
40.0%
0172
20.0%
-172
20.0%
186
 
10.0%
386
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number688
80.0%
Dash Punctuation172
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2344
50.0%
0172
25.0%
186
 
12.5%
386
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common860
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2344
40.0%
0172
20.0%
-172
20.0%
186
 
10.0%
386
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII860
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2344
40.0%
0172
20.0%
-172
20.0%
186
 
10.0%
386
 
10.0%

airtime
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct12
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size816.0 B
nan
59 
20:00
13 
06:00
 
3
12:00
 
2
00:00
 
2
Other values (7)

Length

Max length5
Median length3
Mean length3.627906977
Min length3

Characters and Unicode

Total characters312
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)8.1%

Sample

1st row12:00
2nd row12:00
3rd row10:00
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan59
68.6%
20:0013
 
15.1%
06:003
 
3.5%
12:002
 
2.3%
00:002
 
2.3%
10:001
 
1.2%
18:301
 
1.2%
20:451
 
1.2%
19:001
 
1.2%
20:301
 
1.2%
Other values (2)2
 
2.3%

Length

2022-05-09T21:19:50.249124image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan59
68.6%
20:0013
 
15.1%
06:003
 
3.5%
12:002
 
2.3%
00:002
 
2.3%
10:001
 
1.2%
18:301
 
1.2%
20:451
 
1.2%
19:001
 
1.2%
20:301
 
1.2%
Other values (2)2
 
2.3%

Most occurring characters

ValueCountFrequency (%)
n118
37.8%
073
23.4%
a59
18.9%
:27
 
8.7%
220
 
6.4%
16
 
1.9%
63
 
1.0%
32
 
0.6%
81
 
0.3%
41
 
0.3%
Other values (2)2
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter177
56.7%
Decimal Number108
34.6%
Other Punctuation27
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
073
67.6%
220
 
18.5%
16
 
5.6%
63
 
2.8%
32
 
1.9%
81
 
0.9%
41
 
0.9%
51
 
0.9%
91
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
n118
66.7%
a59
33.3%
Other Punctuation
ValueCountFrequency (%)
:27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin177
56.7%
Common135
43.3%

Most frequent character per script

Common
ValueCountFrequency (%)
073
54.1%
:27
 
20.0%
220
 
14.8%
16
 
4.4%
63
 
2.2%
32
 
1.5%
81
 
0.7%
41
 
0.7%
51
 
0.7%
91
 
0.7%
Latin
ValueCountFrequency (%)
n118
66.7%
a59
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n118
37.8%
073
23.4%
a59
18.9%
:27
 
8.7%
220
 
6.4%
16
 
1.9%
63
 
1.0%
32
 
0.6%
81
 
0.3%
41
 
0.3%
Other values (2)2
 
0.6%

airstamp
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct19
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Memory size816.0 B
2020-12-23T12:00:00+00:00
38 
2020-12-23T03:00:00+00:00
18 
2020-12-23T04:00:00+00:00
2020-12-23T17:00:00+00:00
2020-12-23T11:00:00+00:00
 
3
Other values (14)
17 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2150
Distinct characters12
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)14.0%

Sample

1st row2020-12-23T00:00:00+00:00
2nd row2020-12-23T00:00:00+00:00
3rd row2020-12-23T02:00:00+00:00
4th row2020-12-23T03:00:00+00:00
5th row2020-12-23T03:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-23T12:00:00+00:0038
44.2%
2020-12-23T03:00:00+00:0018
20.9%
2020-12-23T04:00:00+00:005
 
5.8%
2020-12-23T17:00:00+00:005
 
5.8%
2020-12-23T11:00:00+00:003
 
3.5%
2020-12-23T05:00:00+00:003
 
3.5%
2020-12-23T00:00:00+00:002
 
2.3%
2020-12-23T10:00:00+00:001
 
1.2%
2020-12-23T09:30:00+00:001
 
1.2%
2020-12-23T02:00:00+00:001
 
1.2%
Other values (9)9
 
10.5%

Length

2022-05-09T21:19:50.343015image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-23t12:00:00+00:0038
44.2%
2020-12-23t03:00:00+00:0018
20.9%
2020-12-23t04:00:00+00:005
 
5.8%
2020-12-23t17:00:00+00:005
 
5.8%
2020-12-23t11:00:00+00:003
 
3.5%
2020-12-23t05:00:00+00:003
 
3.5%
2020-12-23t00:00:00+00:002
 
2.3%
2020-12-23t19:00:00+00:001
 
1.2%
2020-12-24t01:00:00+00:001
 
1.2%
2020-12-23t22:00:00+00:001
 
1.2%
Other values (9)9
 
10.5%

Most occurring characters

ValueCountFrequency (%)
0893
41.5%
2388
18.0%
:258
 
12.0%
-172
 
8.0%
1141
 
6.6%
3104
 
4.8%
T86
 
4.0%
+86
 
4.0%
48
 
0.4%
76
 
0.3%
Other values (2)8
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1548
72.0%
Other Punctuation258
 
12.0%
Dash Punctuation172
 
8.0%
Uppercase Letter86
 
4.0%
Math Symbol86
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0893
57.7%
2388
25.1%
1141
 
9.1%
3104
 
6.7%
48
 
0.5%
76
 
0.4%
56
 
0.4%
92
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:258
100.0%
Dash Punctuation
ValueCountFrequency (%)
-172
100.0%
Uppercase Letter
ValueCountFrequency (%)
T86
100.0%
Math Symbol
ValueCountFrequency (%)
+86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2064
96.0%
Latin86
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0893
43.3%
2388
18.8%
:258
 
12.5%
-172
 
8.3%
1141
 
6.8%
3104
 
5.0%
+86
 
4.2%
48
 
0.4%
76
 
0.3%
56
 
0.3%
Latin
ValueCountFrequency (%)
T86
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0893
41.5%
2388
18.0%
:258
 
12.0%
-172
 
8.0%
1141
 
6.6%
3104
 
4.8%
T86
 
4.0%
+86
 
4.0%
48
 
0.4%
76
 
0.3%
Other values (2)8
 
0.4%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct32
Distinct (%)40.5%
Missing7
Missing (%)8.1%
Infinite0
Infinite (%)0.0%
Mean33.73417722
Minimum1
Maximum126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-05-09T21:19:50.570271image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.9
Q115
median25
Q345
95-th percentile95.7
Maximum126
Range125
Interquartile range (IQR)30

Descriptive statistics

Standard deviation27.17828548
Coefficient of variation (CV)0.805660245
Kurtosis3.765971174
Mean33.73417722
Median Absolute Deviation (MAD)11
Skewness1.863806904
Sum2665
Variance738.6592016
MonotonicityNot monotonic
2022-05-09T21:19:50.664352image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
4516
18.6%
1511
12.8%
178
 
9.3%
305
 
5.8%
233
 
3.5%
123
 
3.5%
203
 
3.5%
1203
 
3.5%
332
 
2.3%
252
 
2.3%
Other values (22)23
26.7%
(Missing)7
 
8.1%
ValueCountFrequency (%)
11
 
1.2%
21
 
1.2%
31
 
1.2%
41
 
1.2%
51
 
1.2%
61
 
1.2%
123
 
3.5%
131
 
1.2%
141
 
1.2%
1511
12.8%
ValueCountFrequency (%)
1261
 
1.2%
1203
 
3.5%
931
 
1.2%
901
 
1.2%
631
 
1.2%
602
 
2.3%
481
 
1.2%
461
 
1.2%
4516
18.6%
431
 
1.2%

summary
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct15
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size816.0 B
nan
72 
<p>Marco's grand plan shocks Earth, Mars and the Belt.</p>
 
1
<p>It's up to you to decide whether you care about the weather. Your weather girls are here to brighten up your rainy days!</p>
 
1
<p>The promised second part of the House's adventures is better in the Carpathians. This time we go to the capital of the Hutsuls - Verkhona. We will get acquainted with local traditions, talk with those who protect them, and look at a couple of museums. We will rise to the mystical summit of Spitz.</p>
 
1
<p>Kido Butai was the fleet that launched the surprise attack on the US Pacific Fleet at anchor at Pearl Harbor and followed that up with a string of victories in 1942. But how was it commanded, both as a whole and in the high and even mid level command? Today we'll look at that.</p>
 
1
Other values (10)
10 

Length

Max length434
Median length3
Mean length43.81395349
Min length3

Characters and Unicode

Total characters3768
Distinct characters70
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)16.3%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan72
83.7%
<p>Marco's grand plan shocks Earth, Mars and the Belt.</p>1
 
1.2%
<p>It's up to you to decide whether you care about the weather. Your weather girls are here to brighten up your rainy days!</p>1
 
1.2%
<p>The promised second part of the House's adventures is better in the Carpathians. This time we go to the capital of the Hutsuls - Verkhona. We will get acquainted with local traditions, talk with those who protect them, and look at a couple of museums. We will rise to the mystical summit of Spitz.</p>1
 
1.2%
<p>Kido Butai was the fleet that launched the surprise attack on the US Pacific Fleet at anchor at Pearl Harbor and followed that up with a string of victories in 1942. But how was it commanded, both as a whole and in the high and even mid level command? Today we'll look at that.</p>1
 
1.2%
<p>All hail Queen of the Earth herself on this installment of The Expanse Aftershow! Shohreh Aghdashloo aka Chrisjen Avasarala and EP &amp; Writer Dan Nowak join Wes Chatham and Ty Franck to discuss what convinced Shohreh to join The Expanse, Amos' survival instincts, and Under Siege (1992) references.</p>1
 
1.2%
<p>Welcome to the SEASON 2 FINALE of our spooky and FESTIVE show- Too Many Spirits! Join us as we read your submitted holiday ghost stories and enjoy cocktails prepared by freshman bartender, Steven Lim.</p>1
 
1.2%
<p>James's night is not going as planned. On top of it all, Dale conceals a small but significant detail from him.</p>1
 
1.2%
<p>Stephanie tries to recover, and struggles with her reality. Cameron Sr. fights to unify his fractured family while Cameron Jr. follows his ambitions. Brittany senses a rift within her love triangle.</p>1
 
1.2%
<p>In the glory days of Japan's over-the-top MMA events, Kazushi Sakuraba embodied the samurai spirit of PRIDE Fighting Championship. Athletes, personalities and "The Gracie Hunter" himself tell how a pro wrestler became a superstar in the PRIDE ring.</p>1
 
1.2%
Other values (5)5
 
5.8%

Length

2022-05-09T21:19:50.791124image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan72
 
10.8%
the34
 
5.1%
and23
 
3.4%
to20
 
3.0%
of15
 
2.2%
a13
 
1.9%
christmas8
 
1.2%
that7
 
1.0%
with7
 
1.0%
is7
 
1.0%
Other values (363)463
69.2%

Most occurring characters

ValueCountFrequency (%)
583
15.5%
e318
 
8.4%
n311
 
8.3%
a307
 
8.1%
t259
 
6.9%
s190
 
5.0%
i187
 
5.0%
o176
 
4.7%
h168
 
4.5%
r166
 
4.4%
Other values (60)1103
29.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2857
75.8%
Space Separator583
 
15.5%
Uppercase Letter152
 
4.0%
Other Punctuation101
 
2.7%
Math Symbol56
 
1.5%
Decimal Number9
 
0.2%
Dash Punctuation6
 
0.2%
Close Punctuation2
 
0.1%
Open Punctuation2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e318
11.1%
n311
10.9%
a307
10.7%
t259
 
9.1%
s190
 
6.7%
i187
 
6.5%
o176
 
6.2%
h168
 
5.9%
r166
 
5.8%
l119
 
4.2%
Other values (16)656
23.0%
Uppercase Letter
ValueCountFrequency (%)
C19
12.5%
S17
 
11.2%
A13
 
8.6%
E11
 
7.2%
I10
 
6.6%
T9
 
5.9%
M8
 
5.3%
J7
 
4.6%
B7
 
4.6%
G6
 
3.9%
Other values (14)45
29.6%
Other Punctuation
ValueCountFrequency (%)
.32
31.7%
,29
28.7%
'16
15.8%
/14
13.9%
!3
 
3.0%
?2
 
2.0%
"2
 
2.0%
;1
 
1.0%
&1
 
1.0%
:1
 
1.0%
Decimal Number
ValueCountFrequency (%)
93
33.3%
23
33.3%
12
22.2%
41
 
11.1%
Math Symbol
ValueCountFrequency (%)
>28
50.0%
<28
50.0%
Space Separator
ValueCountFrequency (%)
583
100.0%
Dash Punctuation
ValueCountFrequency (%)
-6
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3009
79.9%
Common759
 
20.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e318
 
10.6%
n311
 
10.3%
a307
 
10.2%
t259
 
8.6%
s190
 
6.3%
i187
 
6.2%
o176
 
5.8%
h168
 
5.6%
r166
 
5.5%
l119
 
4.0%
Other values (40)808
26.9%
Common
ValueCountFrequency (%)
583
76.8%
.32
 
4.2%
,29
 
3.8%
>28
 
3.7%
<28
 
3.7%
'16
 
2.1%
/14
 
1.8%
-6
 
0.8%
93
 
0.4%
23
 
0.4%
Other values (10)17
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII3768
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
583
15.5%
e318
 
8.4%
n311
 
8.3%
a307
 
8.1%
t259
 
6.9%
s190
 
5.0%
i187
 
5.0%
o176
 
4.7%
h168
 
4.5%
r166
 
4.4%
Other values (60)1103
29.3%

_embedded_show_id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct62
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47317.9186
Minimum1825
Maximum61755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-05-09T21:19:50.902149image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1825
5-th percentile16871.25
Q147982
median52410.5
Q353192
95-th percentile58144.75
Maximum61755
Range59930
Interquartile range (IQR)5210

Descriptive statistics

Standard deviation12869.52415
Coefficient of variation (CV)0.2719799292
Kurtosis4.340300237
Mean47317.9186
Median Absolute Deviation (MAD)2253.5
Skewness-2.176182892
Sum4069341
Variance165624651.9
MonotonicityNot monotonic
2022-05-09T21:19:50.997385image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
531018
 
9.3%
546648
 
9.3%
521592
 
2.3%
525242
 
2.3%
521042
 
2.3%
217352
 
2.3%
534582
 
2.3%
527432
 
2.3%
586892
 
2.3%
524212
 
2.3%
Other values (52)54
62.8%
ValueCountFrequency (%)
18251
1.2%
22661
1.2%
25041
1.2%
152502
2.3%
217352
2.3%
249631
1.2%
283461
1.2%
306061
1.2%
326801
1.2%
339441
1.2%
ValueCountFrequency (%)
617551
 
1.2%
586892
 
2.3%
584261
 
1.2%
583671
 
1.2%
574781
 
1.2%
567831
 
1.2%
567461
 
1.2%
565311
 
1.2%
550021
 
1.2%
546648
9.3%

_embedded_show_url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct62
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Memory size816.0 B
https://www.tvmaze.com/shows/53101/half-fifty
https://www.tvmaze.com/shows/54664/100-era
https://www.tvmaze.com/shows/52159/to-love
 
2
https://www.tvmaze.com/shows/52524/forever-love
 
2
https://www.tvmaze.com/shows/52104/twisted-fate-of-love
 
2
Other values (57)
64 

Length

Max length69
Median length61
Mean length49.39534884
Min length40

Characters and Unicode

Total characters4248
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)58.1%

Sample

1st rowhttps://www.tvmaze.com/shows/49630/kontakty
2nd rowhttps://www.tvmaze.com/shows/52520/muzskaa-tema
3rd rowhttps://www.tvmaze.com/shows/49652/yi-nian-yong-heng
4th rowhttps://www.tvmaze.com/shows/44276/7-days-of-romance
5th rowhttps://www.tvmaze.com/shows/53101/half-fifty

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/53101/half-fifty8
 
9.3%
https://www.tvmaze.com/shows/54664/100-era8
 
9.3%
https://www.tvmaze.com/shows/52159/to-love2
 
2.3%
https://www.tvmaze.com/shows/52524/forever-love2
 
2.3%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
2.3%
https://www.tvmaze.com/shows/21735/jerks2
 
2.3%
https://www.tvmaze.com/shows/53458/verdens-minste-kommentatorboks2
 
2.3%
https://www.tvmaze.com/shows/52743/the-penalty-zone2
 
2.3%
https://www.tvmaze.com/shows/58689/my-supernatural-power2
 
2.3%
https://www.tvmaze.com/shows/52421/you-complete-me2
 
2.3%
Other values (52)54
62.8%

Length

2022-05-09T21:19:51.122850image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/53101/half-fifty8
 
9.3%
https://www.tvmaze.com/shows/54664/100-era8
 
9.3%
https://www.tvmaze.com/shows/52743/the-penalty-zone2
 
2.3%
https://www.tvmaze.com/shows/52400/dream-detective2
 
2.3%
https://www.tvmaze.com/shows/52421/you-complete-me2
 
2.3%
https://www.tvmaze.com/shows/58689/my-supernatural-power2
 
2.3%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
2.3%
https://www.tvmaze.com/shows/53458/verdens-minste-kommentatorboks2
 
2.3%
https://www.tvmaze.com/shows/21735/jerks2
 
2.3%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
2.3%
Other values (52)54
62.8%

Most occurring characters

ValueCountFrequency (%)
/430
 
10.1%
w361
 
8.5%
t341
 
8.0%
s318
 
7.5%
o251
 
5.9%
e222
 
5.2%
m216
 
5.1%
h213
 
5.0%
a174
 
4.1%
.172
 
4.0%
Other values (30)1550
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2955
69.6%
Other Punctuation688
 
16.2%
Decimal Number458
 
10.8%
Dash Punctuation147
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w361
12.2%
t341
11.5%
s318
10.8%
o251
 
8.5%
e222
 
7.5%
m216
 
7.3%
h213
 
7.2%
a174
 
5.9%
v105
 
3.6%
c104
 
3.5%
Other values (16)650
22.0%
Decimal Number
ValueCountFrequency (%)
584
18.3%
464
14.0%
155
12.0%
252
11.4%
050
10.9%
643
9.4%
733
 
7.2%
332
 
7.0%
827
 
5.9%
918
 
3.9%
Other Punctuation
ValueCountFrequency (%)
/430
62.5%
.172
 
25.0%
:86
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-147
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2955
69.6%
Common1293
30.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
w361
12.2%
t341
11.5%
s318
10.8%
o251
 
8.5%
e222
 
7.5%
m216
 
7.3%
h213
 
7.2%
a174
 
5.9%
v105
 
3.6%
c104
 
3.5%
Other values (16)650
22.0%
Common
ValueCountFrequency (%)
/430
33.3%
.172
 
13.3%
-147
 
11.4%
:86
 
6.7%
584
 
6.5%
464
 
4.9%
155
 
4.3%
252
 
4.0%
050
 
3.9%
643
 
3.3%
Other values (4)110
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII4248
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/430
 
10.1%
w361
 
8.5%
t341
 
8.0%
s318
 
7.5%
o251
 
5.9%
e222
 
5.2%
m216
 
5.1%
h213
 
5.0%
a174
 
4.1%
.172
 
4.0%
Other values (30)1550
36.5%

_embedded_show_name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct62
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Memory size816.0 B
Half-Fifty
100% Era
To Love
 
2
Forever Love
 
2
Twisted Fate of Love
 
2
Other values (57)
64 

Length

Max length35
Median length26
Mean length14.65116279
Min length5

Characters and Unicode

Total characters1260
Distinct characters94
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)58.1%

Sample

1st rowКонтакты
2nd rowМужская тема
3rd rowYi Nian Yong Heng
4th row7 Days of Romance
5th rowHalf-Fifty

Common Values

ValueCountFrequency (%)
Half-Fifty8
 
9.3%
100% Era8
 
9.3%
To Love2
 
2.3%
Forever Love2
 
2.3%
Twisted Fate of Love2
 
2.3%
jerks.2
 
2.3%
Verdens minste kommentatorboks2
 
2.3%
The Penalty Zone2
 
2.3%
My Supernatural Power2
 
2.3%
You Complete Me2
 
2.3%
Other values (52)54
62.8%

Length

2022-05-09T21:19:51.232340image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the9
 
4.0%
half-fifty8
 
3.6%
era8
 
3.6%
love8
 
3.6%
1008
 
3.6%
of7
 
3.1%
my4
 
1.8%
me3
 
1.3%
yi3
 
1.3%
you3
 
1.3%
Other values (142)164
72.9%

Most occurring characters

ValueCountFrequency (%)
139
 
11.0%
e117
 
9.3%
o69
 
5.5%
a68
 
5.4%
r57
 
4.5%
i56
 
4.4%
t54
 
4.3%
n54
 
4.3%
s39
 
3.1%
l32
 
2.5%
Other values (84)575
45.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter865
68.7%
Uppercase Letter199
 
15.8%
Space Separator139
 
11.0%
Decimal Number31
 
2.5%
Other Punctuation18
 
1.4%
Dash Punctuation8
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e117
13.5%
o69
 
8.0%
a68
 
7.9%
r57
 
6.6%
i56
 
6.5%
t54
 
6.2%
n54
 
6.2%
s39
 
4.5%
l32
 
3.7%
h28
 
3.2%
Other values (40)291
33.6%
Uppercase Letter
ValueCountFrequency (%)
T21
 
10.6%
M18
 
9.0%
F17
 
8.5%
S14
 
7.0%
E13
 
6.5%
H12
 
6.0%
L12
 
6.0%
Y11
 
5.5%
A9
 
4.5%
D9
 
4.5%
Other values (22)63
31.7%
Decimal Number
ValueCountFrequency (%)
018
58.1%
19
29.0%
22
 
6.5%
51
 
3.2%
71
 
3.2%
Other Punctuation
ValueCountFrequency (%)
%8
44.4%
:5
27.8%
.3
 
16.7%
,1
 
5.6%
'1
 
5.6%
Space Separator
ValueCountFrequency (%)
139
100.0%
Dash Punctuation
ValueCountFrequency (%)
-8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin973
77.2%
Common196
 
15.6%
Cyrillic91
 
7.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e117
 
12.0%
o69
 
7.1%
a68
 
7.0%
r57
 
5.9%
i56
 
5.8%
t54
 
5.5%
n54
 
5.5%
s39
 
4.0%
l32
 
3.3%
h28
 
2.9%
Other values (41)399
41.0%
Cyrillic
ValueCountFrequency (%)
а10
 
11.0%
т8
 
8.8%
к7
 
7.7%
о7
 
7.7%
р6
 
6.6%
е6
 
6.6%
и4
 
4.4%
с4
 
4.4%
н4
 
4.4%
з3
 
3.3%
Other values (21)32
35.2%
Common
ValueCountFrequency (%)
139
70.9%
018
 
9.2%
19
 
4.6%
-8
 
4.1%
%8
 
4.1%
:5
 
2.6%
.3
 
1.5%
22
 
1.0%
,1
 
0.5%
51
 
0.5%
Other values (2)2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1168
92.7%
Cyrillic91
 
7.2%
None1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
139
 
11.9%
e117
 
10.0%
o69
 
5.9%
a68
 
5.8%
r57
 
4.9%
i56
 
4.8%
t54
 
4.6%
n54
 
4.6%
s39
 
3.3%
l32
 
2.7%
Other values (52)483
41.4%
Cyrillic
ValueCountFrequency (%)
а10
 
11.0%
т8
 
8.8%
к7
 
7.7%
о7
 
7.7%
р6
 
6.6%
е6
 
6.6%
и4
 
4.4%
с4
 
4.4%
н4
 
4.4%
з3
 
3.3%
Other values (21)32
35.2%
None
ValueCountFrequency (%)
ø1
100.0%

_embedded_show_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size816.0 B
Scripted
53 
Talk Show
Animation
Reality
Game Show
 
3
Other values (4)

Length

Max length11
Median length8
Mean length8.081395349
Min length4

Characters and Unicode

Total characters695
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGame Show
2nd rowTalk Show
3rd rowAnimation
4th rowScripted
5th rowScripted

Common Values

ValueCountFrequency (%)
Scripted53
61.6%
Talk Show9
 
10.5%
Animation6
 
7.0%
Reality6
 
7.0%
Game Show3
 
3.5%
Documentary3
 
3.5%
Sports2
 
2.3%
News2
 
2.3%
Variety2
 
2.3%

Length

2022-05-09T21:19:51.326319image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:19:51.453092image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
scripted53
54.1%
show12
 
12.2%
talk9
 
9.2%
animation6
 
6.1%
reality6
 
6.1%
game3
 
3.1%
documentary3
 
3.1%
sports2
 
2.0%
news2
 
2.0%
variety2
 
2.0%

Most occurring characters

ValueCountFrequency (%)
i73
10.5%
t72
10.4%
e69
9.9%
S67
9.6%
r60
8.6%
c56
8.1%
p55
 
7.9%
d53
 
7.6%
a29
 
4.2%
o23
 
3.3%
Other values (17)138
19.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter585
84.2%
Uppercase Letter98
 
14.1%
Space Separator12
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i73
12.5%
t72
12.3%
e69
11.8%
r60
10.3%
c56
9.6%
p55
9.4%
d53
9.1%
a29
 
5.0%
o23
 
3.9%
l15
 
2.6%
Other values (8)80
13.7%
Uppercase Letter
ValueCountFrequency (%)
S67
68.4%
T9
 
9.2%
A6
 
6.1%
R6
 
6.1%
G3
 
3.1%
D3
 
3.1%
N2
 
2.0%
V2
 
2.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin683
98.3%
Common12
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i73
10.7%
t72
10.5%
e69
10.1%
S67
9.8%
r60
8.8%
c56
8.2%
p55
8.1%
d53
7.8%
a29
 
4.2%
o23
 
3.4%
Other values (16)126
18.4%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII695
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i73
10.5%
t72
10.4%
e69
9.9%
S67
9.6%
r60
8.6%
c56
8.1%
p55
 
7.9%
d53
 
7.6%
a29
 
4.2%
o23
 
3.3%
Other values (17)138
19.9%

_embedded_show_language
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct18
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Memory size816.0 B
Korean
19 
Chinese
19 
English
18 
Russian
Norwegian
Other values (13)
20 

Length

Max length10
Median length7
Mean length6.755813953
Min length3

Characters and Unicode

Total characters581
Distinct characters34
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)8.1%

Sample

1st rowRussian
2nd rowRussian
3rd rowChinese
4th rowKorean
5th rowKorean

Common Values

ValueCountFrequency (%)
Korean19
22.1%
Chinese19
22.1%
English18
20.9%
Russian5
 
5.8%
Norwegian5
 
5.8%
nan3
 
3.5%
Ukrainian2
 
2.3%
Japanese2
 
2.3%
Arabic2
 
2.3%
German2
 
2.3%
Other values (8)9
10.5%

Length

2022-05-09T21:19:51.562839image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
korean19
22.1%
chinese19
22.1%
english18
20.9%
russian5
 
5.8%
norwegian5
 
5.8%
nan3
 
3.5%
arabic2
 
2.3%
tagalog2
 
2.3%
german2
 
2.3%
japanese2
 
2.3%
Other values (8)9
10.5%

Most occurring characters

ValueCountFrequency (%)
n85
14.6%
e72
12.4%
i57
9.8%
a55
9.5%
s51
8.8%
h42
 
7.2%
r32
 
5.5%
g28
 
4.8%
o26
 
4.5%
K20
 
3.4%
Other values (24)113
19.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter498
85.7%
Uppercase Letter83
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n85
17.1%
e72
14.5%
i57
11.4%
a55
11.0%
s51
10.2%
h42
8.4%
r32
 
6.4%
g28
 
5.6%
o26
 
5.2%
l20
 
4.0%
Other values (9)30
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
K20
24.1%
C19
22.9%
E18
21.7%
R5
 
6.0%
N5
 
6.0%
T3
 
3.6%
G2
 
2.4%
U2
 
2.4%
A2
 
2.4%
J2
 
2.4%
Other values (5)5
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
Latin581
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n85
14.6%
e72
12.4%
i57
9.8%
a55
9.5%
s51
8.8%
h42
 
7.2%
r32
 
5.5%
g28
 
4.8%
o26
 
4.5%
K20
 
3.4%
Other values (24)113
19.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII581
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n85
14.6%
e72
12.4%
i57
9.8%
a55
9.5%
s51
8.8%
h42
 
7.2%
r32
 
5.5%
g28
 
4.8%
o26
 
4.5%
K20
 
3.4%
Other values (24)113
19.4%

_embedded_show_genres
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct25
Distinct (%)29.1%
Missing0
Missing (%)0.0%
Memory size816.0 B
[]
21 
['Drama', 'Romance']
12 
['Drama']
10 
['Comedy']
10 
['Drama', 'Comedy']
Other values (20)
25 

Length

Max length42
Median length34
Mean length14.8255814
Min length2

Characters and Unicode

Total characters1275
Distinct characters33
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)18.6%

Sample

1st row[]
2nd row[]
3rd row['Comedy', 'Action', 'Anime', 'Fantasy']
4th row['Drama', 'Romance']
5th row['Drama', 'Comedy']

Common Values

ValueCountFrequency (%)
[]21
24.4%
['Drama', 'Romance']12
14.0%
['Drama']10
11.6%
['Comedy']10
11.6%
['Drama', 'Comedy']8
 
9.3%
['Drama', 'Romance', 'History']3
 
3.5%
['Crime', 'Thriller', 'Mystery']2
 
2.3%
['Drama', 'Action', 'Crime']2
 
2.3%
['Drama', 'Fantasy', 'Mystery']2
 
2.3%
['Comedy', 'Supernatural']1
 
1.2%
Other values (15)15
17.4%

Length

2022-05-09T21:19:51.700158image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
drama40
28.0%
comedy24
16.8%
21
14.7%
romance17
11.9%
mystery5
 
3.5%
action5
 
3.5%
history4
 
2.8%
crime4
 
2.8%
fantasy4
 
2.8%
family3
 
2.1%
Other values (10)16
 
11.2%

Most occurring characters

ValueCountFrequency (%)
'244
19.1%
a114
 
8.9%
m91
 
7.1%
[86
 
6.7%
]86
 
6.7%
r69
 
5.4%
e65
 
5.1%
,57
 
4.5%
57
 
4.5%
o52
 
4.1%
Other values (23)354
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter621
48.7%
Other Punctuation301
23.6%
Uppercase Letter123
 
9.6%
Open Punctuation86
 
6.7%
Close Punctuation86
 
6.7%
Space Separator57
 
4.5%
Dash Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a114
18.4%
m91
14.7%
r69
11.1%
e65
10.5%
o52
8.4%
y45
 
7.2%
n36
 
5.8%
i28
 
4.5%
d27
 
4.3%
c26
 
4.2%
Other values (7)68
11.0%
Uppercase Letter
ValueCountFrequency (%)
D40
32.5%
C30
24.4%
R17
13.8%
A9
 
7.3%
F8
 
6.5%
M6
 
4.9%
T4
 
3.3%
S4
 
3.3%
H4
 
3.3%
W1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
'244
81.1%
,57
 
18.9%
Open Punctuation
ValueCountFrequency (%)
[86
100.0%
Close Punctuation
ValueCountFrequency (%)
]86
100.0%
Space Separator
ValueCountFrequency (%)
57
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin744
58.4%
Common531
41.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a114
15.3%
m91
12.2%
r69
 
9.3%
e65
 
8.7%
o52
 
7.0%
y45
 
6.0%
D40
 
5.4%
n36
 
4.8%
C30
 
4.0%
i28
 
3.8%
Other values (17)174
23.4%
Common
ValueCountFrequency (%)
'244
46.0%
[86
 
16.2%
]86
 
16.2%
,57
 
10.7%
57
 
10.7%
-1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII1275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'244
19.1%
a114
 
8.9%
m91
 
7.1%
[86
 
6.7%
]86
 
6.7%
r69
 
5.4%
e65
 
5.1%
,57
 
4.5%
57
 
4.5%
o52
 
4.1%
Other values (23)354
27.8%

_embedded_show_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size816.0 B
Ended
44 
Running
36 
To Be Determined

Length

Max length16
Median length5
Mean length6.604651163
Min length5

Characters and Unicode

Total characters568
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowRunning
4th rowEnded
5th rowEnded

Common Values

ValueCountFrequency (%)
Ended44
51.2%
Running36
41.9%
To Be Determined6
 
7.0%

Length

2022-05-09T21:19:51.802923image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:19:51.906894image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
ended44
44.9%
running36
36.7%
to6
 
6.1%
be6
 
6.1%
determined6
 
6.1%

Most occurring characters

ValueCountFrequency (%)
n158
27.8%
d94
16.5%
e68
12.0%
E44
 
7.7%
i42
 
7.4%
R36
 
6.3%
u36
 
6.3%
g36
 
6.3%
12
 
2.1%
T6
 
1.1%
Other values (6)36
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter458
80.6%
Uppercase Letter98
 
17.3%
Space Separator12
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n158
34.5%
d94
20.5%
e68
14.8%
i42
 
9.2%
u36
 
7.9%
g36
 
7.9%
o6
 
1.3%
t6
 
1.3%
r6
 
1.3%
m6
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
E44
44.9%
R36
36.7%
T6
 
6.1%
B6
 
6.1%
D6
 
6.1%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin556
97.9%
Common12
 
2.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n158
28.4%
d94
16.9%
e68
12.2%
E44
 
7.9%
i42
 
7.6%
R36
 
6.5%
u36
 
6.5%
g36
 
6.5%
T6
 
1.1%
o6
 
1.1%
Other values (5)30
 
5.4%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n158
27.8%
d94
16.5%
e68
12.0%
E44
 
7.7%
i42
 
7.4%
R36
 
6.3%
u36
 
6.3%
g36
 
6.3%
12
 
2.1%
T6
 
1.1%
Other values (6)36
 
6.3%

_embedded_show_runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct18
Distinct (%)26.5%
Missing18
Missing (%)20.9%
Infinite0
Infinite (%)0.0%
Mean35.22058824
Minimum2
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-05-09T21:19:51.981892image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile10.7
Q117
median27.5
Q345
95-th percentile109.5
Maximum120
Range118
Interquartile range (IQR)28

Descriptive statistics

Standard deviation27.53822071
Coefficient of variation (CV)0.7818785002
Kurtosis3.452680944
Mean35.22058824
Median Absolute Deviation (MAD)12.5
Skewness1.871452666
Sum2395
Variance758.3535996
MonotonicityNot monotonic
2022-05-09T21:19:52.076372image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
4516
18.6%
159
10.5%
308
9.3%
178
9.3%
205
 
5.8%
1204
 
4.7%
233
 
3.5%
253
 
3.5%
902
 
2.3%
602
 
2.3%
Other values (8)8
9.3%
(Missing)18
20.9%
ValueCountFrequency (%)
21
 
1.2%
41
 
1.2%
51
 
1.2%
101
 
1.2%
121
 
1.2%
159
10.5%
178
9.3%
191
 
1.2%
205
5.8%
233
 
3.5%
ValueCountFrequency (%)
1204
 
4.7%
902
 
2.3%
602
 
2.3%
551
 
1.2%
4516
18.6%
331
 
1.2%
308
9.3%
253
 
3.5%
233
 
3.5%
205
 
5.8%

_embedded_show_averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct32
Distinct (%)39.5%
Missing5
Missing (%)5.8%
Infinite0
Infinite (%)0.0%
Mean32.24691358
Minimum2
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-05-09T21:19:52.168697image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q115
median25
Q345
95-th percentile90
Maximum120
Range118
Interquartile range (IQR)30

Descriptive statistics

Standard deviation24.98275949
Coefficient of variation (CV)0.7747333532
Kurtosis3.663546261
Mean32.24691358
Median Absolute Deviation (MAD)10
Skewness1.801367101
Sum2612
Variance624.1382716
MonotonicityNot monotonic
2022-05-09T21:19:52.278292image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
4514
16.3%
1510
11.6%
178
 
9.3%
256
 
7.0%
205
 
5.8%
305
 
5.8%
123
 
3.5%
32
 
2.3%
602
 
2.3%
242
 
2.3%
Other values (22)24
27.9%
(Missing)5
 
5.8%
ValueCountFrequency (%)
21
 
1.2%
32
 
2.3%
41
 
1.2%
51
 
1.2%
91
 
1.2%
102
 
2.3%
123
 
3.5%
141
 
1.2%
1510
11.6%
178
9.3%
ValueCountFrequency (%)
1202
 
2.3%
1101
 
1.2%
971
 
1.2%
901
 
1.2%
751
 
1.2%
602
 
2.3%
591
 
1.2%
551
 
1.2%
491
 
1.2%
4514
16.3%

_embedded_show_premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct53
Distinct (%)61.6%
Missing0
Missing (%)0.0%
Memory size816.0 B
2020-12-23
17 
2020-12-16
 
4
2020-11-19
 
3
2020-12-08
 
3
2020-11-18
 
3
Other values (48)
56 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters860
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)47.7%

Sample

1st row2019-04-03
2nd row2020-12-17
3rd row2020-08-12
4th row2019-10-08
5th row2020-12-23

Common Values

ValueCountFrequency (%)
2020-12-2317
 
19.8%
2020-12-164
 
4.7%
2020-11-193
 
3.5%
2020-12-083
 
3.5%
2020-11-183
 
3.5%
2020-12-143
 
3.5%
2020-11-232
 
2.3%
2017-02-102
 
2.3%
2013-12-242
 
2.3%
2017-01-262
 
2.3%
Other values (43)45
52.3%

Length

2022-05-09T21:19:52.389613image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-2317
 
19.8%
2020-12-164
 
4.7%
2020-11-193
 
3.5%
2020-12-083
 
3.5%
2020-11-183
 
3.5%
2020-12-143
 
3.5%
2017-01-262
 
2.3%
2020-12-212
 
2.3%
2020-12-022
 
2.3%
2013-12-242
 
2.3%
Other values (43)45
52.3%

Most occurring characters

ValueCountFrequency (%)
2224
26.0%
0200
23.3%
-172
20.0%
1150
17.4%
327
 
3.1%
920
 
2.3%
819
 
2.2%
416
 
1.9%
712
 
1.4%
610
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number688
80.0%
Dash Punctuation172
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2224
32.6%
0200
29.1%
1150
21.8%
327
 
3.9%
920
 
2.9%
819
 
2.8%
416
 
2.3%
712
 
1.7%
610
 
1.5%
510
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
-172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common860
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2224
26.0%
0200
23.3%
-172
20.0%
1150
17.4%
327
 
3.1%
920
 
2.3%
819
 
2.2%
416
 
1.9%
712
 
1.4%
610
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII860
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2224
26.0%
0200
23.3%
-172
20.0%
1150
17.4%
327
 
3.1%
920
 
2.3%
819
 
2.2%
416
 
1.9%
712
 
1.4%
610
 
1.2%

_embedded_show_ended
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct18
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Memory size816.0 B
nan
42 
2020-12-23
18 
2020-12-30
2021-01-05
 
4
2021-01-20
 
2
Other values (13)
15 

Length

Max length10
Median length10
Mean length6.581395349
Min length3

Characters and Unicode

Total characters566
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)12.8%

Sample

1st rownan
2nd row2020-12-25
3rd rownan
4th row2021-01-20
5th row2020-12-23

Common Values

ValueCountFrequency (%)
nan42
48.8%
2020-12-2318
20.9%
2020-12-305
 
5.8%
2021-01-054
 
4.7%
2021-01-202
 
2.3%
2021-01-142
 
2.3%
2021-01-272
 
2.3%
2021-02-031
 
1.2%
2021-06-181
 
1.2%
2020-12-281
 
1.2%
Other values (8)8
 
9.3%

Length

2022-05-09T21:19:52.566932image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan42
48.8%
2020-12-2318
20.9%
2020-12-305
 
5.8%
2021-01-054
 
4.7%
2021-01-202
 
2.3%
2021-01-142
 
2.3%
2021-01-272
 
2.3%
2022-01-141
 
1.2%
2021-01-061
 
1.2%
2020-12-311
 
1.2%
Other values (8)8
 
9.3%

Most occurring characters

ValueCountFrequency (%)
2144
25.4%
0102
18.0%
-88
15.5%
n84
14.8%
161
10.8%
a42
 
7.4%
329
 
5.1%
55
 
0.9%
44
 
0.7%
63
 
0.5%
Other values (2)4
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number352
62.2%
Lowercase Letter126
 
22.3%
Dash Punctuation88
 
15.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2144
40.9%
0102
29.0%
161
17.3%
329
 
8.2%
55
 
1.4%
44
 
1.1%
63
 
0.9%
72
 
0.6%
82
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
n84
66.7%
a42
33.3%
Dash Punctuation
ValueCountFrequency (%)
-88
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common440
77.7%
Latin126
 
22.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2144
32.7%
0102
23.2%
-88
20.0%
161
13.9%
329
 
6.6%
55
 
1.1%
44
 
0.9%
63
 
0.7%
72
 
0.5%
82
 
0.5%
Latin
ValueCountFrequency (%)
n84
66.7%
a42
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII566
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2144
25.4%
0102
18.0%
-88
15.5%
n84
14.8%
161
10.8%
a42
 
7.4%
329
 
5.1%
55
 
0.9%
44
 
0.7%
63
 
0.5%
Other values (2)4
 
0.7%

_embedded_show_officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct54
Distinct (%)62.8%
Missing0
Missing (%)0.0%
Memory size816.0 B
nan
18 
https://www.wavve.com/player/vod?programid=C9901_C99000000049
https://so.youku.com/search_video/q_%20%E6%9C%80%E5%88%9D%E7%9A%84%E7%9B%B8%E9%81%87?searchfrom=1
 
2
https://tv.nrk.no/serie/verdens-minste-kommentatorboks
 
2
https://v.qq.com/detail/m/mzc00200ur8p8zp.html
 
2
Other values (49)
54 

Length

Max length97
Median length72
Mean length41.19767442
Min length3

Characters and Unicode

Total characters3543
Distinct characters74
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)51.2%

Sample

1st rowhttps://www.youtube.com/playlist?list=PLZ1FUdedsrSJubWkFFh5vKHzawzQk1mYI
2nd rowhttps://www.ivi.ru/watch/muzhskaya-tema
3rd rowhttps://v.qq.com/detail/w/ww18u675tfmhas6.html
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan18
20.9%
https://www.wavve.com/player/vod?programid=C9901_C990000000498
 
9.3%
https://so.youku.com/search_video/q_%20%E6%9C%80%E5%88%9D%E7%9A%84%E7%9B%B8%E9%81%87?searchfrom=12
 
2.3%
https://tv.nrk.no/serie/verdens-minste-kommentatorboks2
 
2.3%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html2
 
2.3%
https://www.tytnetwork.com2
 
2.3%
https://www.joyn.de/serien/jerks2
 
2.3%
https://www.iqiyi.com/a_19rrhllpip.html2
 
2.3%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
2.3%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=2
 
2.3%
Other values (44)44
51.2%

Length

2022-05-09T21:19:52.692763image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan18
20.9%
https://www.wavve.com/player/vod?programid=c9901_c990000000498
 
9.3%
https://www.joyn.de/serien/jerks2
 
2.3%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
2.3%
https://www.iqiyi.com/a_19rrhllpip.html2
 
2.3%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab2
 
2.3%
https://www.tytnetwork.com2
 
2.3%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html2
 
2.3%
https://tv.nrk.no/serie/verdens-minste-kommentatorboks2
 
2.3%
https://so.youku.com/search_video/q_%20%e6%9c%80%e5%88%9d%e7%9a%84%e7%9b%b8%e9%81%87?searchfrom=12
 
2.3%
Other values (44)44
51.2%

Most occurring characters

ValueCountFrequency (%)
/272
 
7.7%
t243
 
6.9%
w160
 
4.5%
o159
 
4.5%
s158
 
4.5%
e142
 
4.0%
.136
 
3.8%
a128
 
3.6%
h125
 
3.5%
p124
 
3.5%
Other values (64)1896
53.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2272
64.1%
Other Punctuation563
 
15.9%
Decimal Number369
 
10.4%
Uppercase Letter262
 
7.4%
Math Symbol30
 
0.8%
Dash Punctuation28
 
0.8%
Connector Punctuation19
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t243
 
10.7%
w160
 
7.0%
o159
 
7.0%
s158
 
7.0%
e142
 
6.2%
a128
 
5.6%
h125
 
5.5%
p124
 
5.5%
m117
 
5.1%
n106
 
4.7%
Other values (16)810
35.7%
Uppercase Letter
ValueCountFrequency (%)
C27
 
10.3%
E24
 
9.2%
B20
 
7.6%
L14
 
5.3%
P14
 
5.3%
A13
 
5.0%
Y12
 
4.6%
H12
 
4.6%
S10
 
3.8%
Q10
 
3.8%
Other values (16)106
40.5%
Decimal Number
ValueCountFrequency (%)
0100
27.1%
972
19.5%
141
11.1%
833
 
8.9%
530
 
8.1%
426
 
7.0%
621
 
5.7%
218
 
4.9%
717
 
4.6%
311
 
3.0%
Other Punctuation
ValueCountFrequency (%)
/272
48.3%
.136
24.2%
:68
 
12.1%
%57
 
10.1%
?21
 
3.7%
&7
 
1.2%
#1
 
0.2%
!1
 
0.2%
Math Symbol
ValueCountFrequency (%)
=28
93.3%
+2
 
6.7%
Dash Punctuation
ValueCountFrequency (%)
-28
100.0%
Connector Punctuation
ValueCountFrequency (%)
_19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2534
71.5%
Common1009
 
28.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t243
 
9.6%
w160
 
6.3%
o159
 
6.3%
s158
 
6.2%
e142
 
5.6%
a128
 
5.1%
h125
 
4.9%
p124
 
4.9%
m117
 
4.6%
n106
 
4.2%
Other values (42)1072
42.3%
Common
ValueCountFrequency (%)
/272
27.0%
.136
13.5%
0100
 
9.9%
972
 
7.1%
:68
 
6.7%
%57
 
5.6%
141
 
4.1%
833
 
3.3%
530
 
3.0%
-28
 
2.8%
Other values (12)172
17.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3543
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/272
 
7.7%
t243
 
6.9%
w160
 
4.5%
o159
 
4.5%
s158
 
4.5%
e142
 
4.0%
.136
 
3.8%
a128
 
3.6%
h125
 
3.5%
p124
 
3.5%
Other values (64)1896
53.5%

_embedded_show_weight
Real number (ℝ≥0)

HIGH CORRELATION

Distinct43
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.40697674
Minimum2
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-05-09T21:19:52.830921image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.25
Q117.25
median20
Q341
95-th percentile85
Maximum99
Range97
Interquartile range (IQR)23.75

Descriptive statistics

Standard deviation25.55242726
Coefficient of variation (CV)0.8135907977
Kurtosis0.3169311042
Mean31.40697674
Median Absolute Deviation (MAD)10
Skewness1.177955609
Sum2701
Variance652.926539
MonotonicityNot monotonic
2022-05-09T21:19:52.951197image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
199
 
10.5%
209
 
10.5%
187
 
8.1%
85
 
5.8%
64
 
4.7%
413
 
3.5%
293
 
3.5%
22
 
2.3%
252
 
2.3%
302
 
2.3%
Other values (33)40
46.5%
ValueCountFrequency (%)
22
 
2.3%
32
 
2.3%
51
 
1.2%
64
4.7%
71
 
1.2%
85
5.8%
102
 
2.3%
141
 
1.2%
152
 
2.3%
172
 
2.3%
ValueCountFrequency (%)
991
1.2%
981
1.2%
921
1.2%
881
1.2%
861
1.2%
821
1.2%
791
1.2%
772
2.3%
761
1.2%
731
1.2%

_embedded_show_dvdCountry
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size816.0 B
nan
85 
{'name': 'Ukraine', 'code': 'UA', 'timezone': 'Europe/Zaporozhye'}
 
1

Length

Max length66
Median length3
Mean length3.73255814
Min length3

Characters and Unicode

Total characters321
Distinct characters27
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan85
98.8%
{'name': 'Ukraine', 'code': 'UA', 'timezone': 'Europe/Zaporozhye'}1
 
1.2%

Length

2022-05-09T21:19:53.069137image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:19:53.154880image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan85
93.4%
name1
 
1.1%
ukraine1
 
1.1%
code1
 
1.1%
ua1
 
1.1%
timezone1
 
1.1%
europe/zaporozhye1
 
1.1%

Most occurring characters

ValueCountFrequency (%)
n173
53.9%
a88
27.4%
'12
 
3.7%
e7
 
2.2%
o5
 
1.6%
5
 
1.6%
:3
 
0.9%
r3
 
0.9%
i2
 
0.6%
p2
 
0.6%
Other values (17)21
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter291
90.7%
Other Punctuation18
 
5.6%
Space Separator5
 
1.6%
Uppercase Letter5
 
1.6%
Open Punctuation1
 
0.3%
Close Punctuation1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n173
59.5%
a88
30.2%
e7
 
2.4%
o5
 
1.7%
r3
 
1.0%
i2
 
0.7%
p2
 
0.7%
z2
 
0.7%
m2
 
0.7%
u1
 
0.3%
Other values (6)6
 
2.1%
Other Punctuation
ValueCountFrequency (%)
'12
66.7%
:3
 
16.7%
,2
 
11.1%
/1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
U2
40.0%
Z1
20.0%
E1
20.0%
A1
20.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
{1
100.0%
Close Punctuation
ValueCountFrequency (%)
}1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin296
92.2%
Common25
 
7.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n173
58.4%
a88
29.7%
e7
 
2.4%
o5
 
1.7%
r3
 
1.0%
i2
 
0.7%
p2
 
0.7%
z2
 
0.7%
U2
 
0.7%
m2
 
0.7%
Other values (10)10
 
3.4%
Common
ValueCountFrequency (%)
'12
48.0%
5
20.0%
:3
 
12.0%
,2
 
8.0%
/1
 
4.0%
{1
 
4.0%
}1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII321
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n173
53.9%
a88
27.4%
'12
 
3.7%
e7
 
2.2%
o5
 
1.6%
5
 
1.6%
:3
 
0.9%
r3
 
0.9%
i2
 
0.6%
p2
 
0.6%
Other values (17)21
 
6.5%

_embedded_show_summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct54
Distinct (%)62.8%
Missing0
Missing (%)0.0%
Memory size816.0 B
nan
<p><b>Half-Fifty</b> is a comedy drama about youth and growth, and the series follows a group of 25-year-olds who end up in the world of YouTubers.</p>
<p><b>100% Era</b> imagines the post-corona future. How the lives of kids born during the pandemic will look like? What will humanity and teens look like in 2044? Our teenagers living in a more competitive world, where the world no longer needs human hands. For humans, the competition to rise to the top is intensifying. How to secretly love children in the era when schools disappeared and contactless. Hee Jae and Shi Dae attend the same top rank education academy. It focuses on training kids to score 100% on tests, while kids who score below 90% get expelled. In such an environment, Shi Dae and Hee Jae spend their teenage years and grow together.</p>
<p>Comedians comment on pedestrians and casual passers-by from the world's smallest commentator box.</p>
 
2
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>
 
2
Other values (49)
57 

Length

Max length807
Median length505
Mean length312.2906977
Min length3

Characters and Unicode

Total characters26857
Distinct characters96
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)47.7%

Sample

1st rownan
2nd row<p><b>Мужская тема</b> is a symbiosis of talk shows and modern podcasts, where male celebrities answer questions that concern people in the XXI century. Bright representatives of show business, theater, pop, cinema, sports, as well as Internet stars meet in the barbershop. Here, on male territory, they can openly discuss a variety of topics, sometimes seriously, and sometimes with humor. This is a chance to see the idol in a confidential communication without notes, compare his opinion with your own and hear what men really talk about when there is not a single girl around.</p>
3rd row<p>One will to create oceans. One will to summon the mulberry fields.<br /><br />One will to slaughter countless devils. One will to eradicate innumerable immortals.<br /><br />Only my will… is eternal.<br /><br />A Will Eternal tells the tale of Bai Xiaochun, an endearing but exasperating young man who is driven primarily by his fear of death and desire to live forever, but who deeply values friendship and family.<br /><br />(Source: Novel Updates)</p>
4th row<p>Da Eun works part-time and Kim Byul is an idol in her 5th years since debut. These two girls who look alike decide to change each other's lives just for 7 days. It tells the romantic encounters of these 2 girls.</p>
5th row<p><b>Half-Fifty</b> is a comedy drama about youth and growth, and the series follows a group of 25-year-olds who end up in the world of YouTubers.</p>

Common Values

ValueCountFrequency (%)
nan9
 
10.5%
<p><b>Half-Fifty</b> is a comedy drama about youth and growth, and the series follows a group of 25-year-olds who end up in the world of YouTubers.</p>8
 
9.3%
<p><b>100% Era</b> imagines the post-corona future. How the lives of kids born during the pandemic will look like? What will humanity and teens look like in 2044? Our teenagers living in a more competitive world, where the world no longer needs human hands. For humans, the competition to rise to the top is intensifying. How to secretly love children in the era when schools disappeared and contactless. Hee Jae and Shi Dae attend the same top rank education academy. It focuses on training kids to score 100% on tests, while kids who score below 90% get expelled. In such an environment, Shi Dae and Hee Jae spend their teenage years and grow together.</p>8
 
9.3%
<p>Comedians comment on pedestrians and casual passers-by from the world's smallest commentator box.</p>2
 
2.3%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>2
 
2.3%
<p>Two unlikely individuals join forces to find the truth behind a series of murders using an unconventional method. Chen Si, a female detective with a sense of justice, unexpectedly becomess partners with Yuan Shuai, a dream interpreter with a dark past.</p>2
 
2.3%
<p>‎At the end of the 20th century, due to the sudden decision of Xin Shensheng, gao Shan's business went bankrupt. Gao Shan wants to prove his father's innocence, but on his way suddenly falls in love with the daughter of Xin Shensheng, Tsin Waugh. Learning about the intentions of Gao Shan, Xin Shansheng makes him quit his job. ‎<br /><br />‎Gao Shan decides to go to Hong Kong to start from scratch, where he meets a benefactor and earns his first million in his life. Under the guidance of a mentor, he goes to Beijing and becomes a well-known investor. Soon Gao Shan meets Tsin Vo, who became a financial headhunter. Can love help them find their way to each other again? ‎<br /><br />‎Based on the novel by Xiao Moli "Little Storm 1.0"‎</p>2
 
2.3%
<p>A story that follows two people's brave pursuit of love from their campus days to their humble beginnings as they enter the workplace to chase after their dreams together.</p>2
 
2.3%
<p>A story that follows undercover cop Gan Tian Lei who spent 10 years of his life walking a gray area. After waking up from a serious injury, he restarts his life and tries to solve a case by relying on his lost memories.</p>2
 
2.3%
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>2
 
2.3%
Other values (44)47
54.7%

Length

2022-05-09T21:19:53.264844image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the240
 
5.3%
and163
 
3.6%
a133
 
3.0%
to132
 
2.9%
of113
 
2.5%
in110
 
2.4%
is40
 
0.9%
on39
 
0.9%
who39
 
0.9%
his37
 
0.8%
Other values (1357)3446
76.7%

Most occurring characters

ValueCountFrequency (%)
4399
16.4%
e2570
 
9.6%
a1613
 
6.0%
t1609
 
6.0%
n1581
 
5.9%
o1569
 
5.8%
i1434
 
5.3%
s1348
 
5.0%
r1258
 
4.7%
h1013
 
3.8%
Other values (86)8463
31.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter20141
75.0%
Space Separator4406
 
16.4%
Uppercase Letter817
 
3.0%
Other Punctuation719
 
2.7%
Math Symbol516
 
1.9%
Decimal Number147
 
0.5%
Dash Punctuation86
 
0.3%
Format12
 
< 0.1%
Open Punctuation6
 
< 0.1%
Close Punctuation6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2570
12.8%
a1613
 
8.0%
t1609
 
8.0%
n1581
 
7.8%
o1569
 
7.8%
i1434
 
7.1%
s1348
 
6.7%
r1258
 
6.2%
h1013
 
5.0%
l838
 
4.2%
Other values (30)5308
26.4%
Uppercase Letter
ValueCountFrequency (%)
S89
 
10.9%
H74
 
9.1%
T55
 
6.7%
A46
 
5.6%
D46
 
5.6%
W46
 
5.6%
F44
 
5.4%
Y39
 
4.8%
M37
 
4.5%
J35
 
4.3%
Other values (17)306
37.5%
Other Punctuation
ValueCountFrequency (%)
.245
34.1%
,223
31.0%
/138
19.2%
'40
 
5.6%
%24
 
3.3%
?19
 
2.6%
"18
 
2.5%
:6
 
0.8%
!5
 
0.7%
1
 
0.1%
Decimal Number
ValueCountFrequency (%)
059
40.1%
225
17.0%
122
 
15.0%
416
 
10.9%
510
 
6.8%
98
 
5.4%
85
 
3.4%
72
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
-78
90.7%
7
 
8.1%
1
 
1.2%
Space Separator
ValueCountFrequency (%)
4399
99.8%
 7
 
0.2%
Math Symbol
ValueCountFrequency (%)
<258
50.0%
>258
50.0%
Format
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
(6
100.0%
Close Punctuation
ValueCountFrequency (%)
)6
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin20947
78.0%
Common5899
 
22.0%
Cyrillic11
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2570
12.3%
a1613
 
7.7%
t1609
 
7.7%
n1581
 
7.5%
o1569
 
7.5%
i1434
 
6.8%
s1348
 
6.4%
r1258
 
6.0%
h1013
 
4.8%
l838
 
4.0%
Other values (47)6114
29.2%
Common
ValueCountFrequency (%)
4399
74.6%
<258
 
4.4%
>258
 
4.4%
.245
 
4.2%
,223
 
3.8%
/138
 
2.3%
-78
 
1.3%
059
 
1.0%
'40
 
0.7%
225
 
0.4%
Other values (19)176
 
3.0%
Cyrillic
ValueCountFrequency (%)
а2
18.2%
с1
9.1%
к1
9.1%
ж1
9.1%
я1
9.1%
т1
9.1%
е1
9.1%
м1
9.1%
у1
9.1%
М1
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII26800
99.8%
None25
 
0.1%
Punctuation21
 
0.1%
Cyrillic11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4399
16.4%
e2570
 
9.6%
a1613
 
6.0%
t1609
 
6.0%
n1581
 
5.9%
o1569
 
5.9%
i1434
 
5.4%
s1348
 
5.0%
r1258
 
4.7%
h1013
 
3.8%
Other values (66)8406
31.4%
Punctuation
ValueCountFrequency (%)
12
57.1%
7
33.3%
1
 
4.8%
1
 
4.8%
None
ValueCountFrequency (%)
ä8
32.0%
 7
28.0%
ü6
24.0%
ß2
 
8.0%
å1
 
4.0%
é1
 
4.0%
Cyrillic
ValueCountFrequency (%)
а2
18.2%
с1
9.1%
к1
9.1%
ж1
9.1%
я1
9.1%
т1
9.1%
е1
9.1%
м1
9.1%
у1
9.1%
М1
9.1%

_embedded_show_updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct62
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1630801143
Minimum1609060726
Maximum1652080636
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-05-09T21:19:53.402690image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1609060726
5-th percentile1609799896
Q11612570586
median1629571716
Q31647813141
95-th percentile1651754997
Maximum1652080636
Range43019910
Interquartile range (IQR)35242555.25

Descriptive statistics

Standard deviation16130453.62
Coefficient of variation (CV)0.009891122342
Kurtosis-1.661489052
Mean1630801143
Median Absolute Deviation (MAD)17093571
Skewness-0.01198066454
Sum1.402488983 × 1011
Variance2.60191534 × 1014
MonotonicityNot monotonic
2022-05-09T21:19:53.512341image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16115091688
 
9.3%
16295717168
 
9.3%
16090607262
 
2.3%
16124781452
 
2.3%
16095351412
 
2.3%
16442552222
 
2.3%
16179668322
 
2.3%
16097998962
 
2.3%
16357351792
 
2.3%
16196334992
 
2.3%
Other values (52)54
62.8%
ValueCountFrequency (%)
16090607262
 
2.3%
16095351412
 
2.3%
16097998962
 
2.3%
16108903401
 
1.2%
16111891791
 
1.2%
16114368421
 
1.2%
16115091688
9.3%
16120078311
 
1.2%
16123781171
 
1.2%
16124781452
 
2.3%
ValueCountFrequency (%)
16520806361
1.2%
16519339621
1.2%
16519332091
1.2%
16518386471
1.2%
16517773161
1.2%
16516880411
1.2%
16516456841
1.2%
16515250021
1.2%
16512533561
1.2%
16509836761
1.2%

_links_self_href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct86
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size816.0 B
https://api.tvmaze.com/episodes/1977902
 
1
https://api.tvmaze.com/episodes/1950369
 
1
https://api.tvmaze.com/episodes/1998678
 
1
https://api.tvmaze.com/episodes/1998676
 
1
https://api.tvmaze.com/episodes/1998675
 
1
Other values (81)
81 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3354
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977902
2nd rowhttps://api.tvmaze.com/episodes/2015818
3rd rowhttps://api.tvmaze.com/episodes/1964000
4th rowhttps://api.tvmaze.com/episodes/1995405
5th rowhttps://api.tvmaze.com/episodes/2007760

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
1.2%
https://api.tvmaze.com/episodes/19503691
 
1.2%
https://api.tvmaze.com/episodes/19986781
 
1.2%
https://api.tvmaze.com/episodes/19986761
 
1.2%
https://api.tvmaze.com/episodes/19986751
 
1.2%
https://api.tvmaze.com/episodes/19986741
 
1.2%
https://api.tvmaze.com/episodes/19986731
 
1.2%
https://api.tvmaze.com/episodes/19978151
 
1.2%
https://api.tvmaze.com/episodes/19978141
 
1.2%
https://api.tvmaze.com/episodes/20833311
 
1.2%
Other values (76)76
88.4%

Length

2022-05-09T21:19:53.618312image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
1.2%
https://api.tvmaze.com/episodes/23244291
 
1.2%
https://api.tvmaze.com/episodes/19954051
 
1.2%
https://api.tvmaze.com/episodes/20077601
 
1.2%
https://api.tvmaze.com/episodes/19857891
 
1.2%
https://api.tvmaze.com/episodes/20396221
 
1.2%
https://api.tvmaze.com/episodes/20396231
 
1.2%
https://api.tvmaze.com/episodes/23244271
 
1.2%
https://api.tvmaze.com/episodes/23244281
 
1.2%
https://api.tvmaze.com/episodes/20158371
 
1.2%
Other values (76)76
88.4%

Most occurring characters

ValueCountFrequency (%)
/344
 
10.3%
p258
 
7.7%
s258
 
7.7%
e258
 
7.7%
t258
 
7.7%
o172
 
5.1%
a172
 
5.1%
i172
 
5.1%
.172
 
5.1%
m172
 
5.1%
Other values (16)1118
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2150
64.1%
Other Punctuation602
 
17.9%
Decimal Number602
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p258
12.0%
s258
12.0%
e258
12.0%
t258
12.0%
o172
8.0%
a172
8.0%
i172
8.0%
m172
8.0%
h86
 
4.0%
d86
 
4.0%
Other values (3)258
12.0%
Decimal Number
ValueCountFrequency (%)
9109
18.1%
292
15.3%
181
13.5%
357
9.5%
055
9.1%
850
8.3%
644
7.3%
441
 
6.8%
738
 
6.3%
535
 
5.8%
Other Punctuation
ValueCountFrequency (%)
/344
57.1%
.172
28.6%
:86
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2150
64.1%
Common1204
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/344
28.6%
.172
14.3%
9109
 
9.1%
292
 
7.6%
:86
 
7.1%
181
 
6.7%
357
 
4.7%
055
 
4.6%
850
 
4.2%
644
 
3.7%
Other values (3)114
 
9.5%
Latin
ValueCountFrequency (%)
p258
12.0%
s258
12.0%
e258
12.0%
t258
12.0%
o172
8.0%
a172
8.0%
i172
8.0%
m172
8.0%
h86
 
4.0%
d86
 
4.0%
Other values (3)258
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3354
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/344
 
10.3%
p258
 
7.7%
s258
 
7.7%
e258
 
7.7%
t258
 
7.7%
o172
 
5.1%
a172
 
5.1%
i172
 
5.1%
.172
 
5.1%
m172
 
5.1%
Other values (16)1118
33.3%

Interactions

2022-05-09T21:19:45.554200image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:25.608275image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:30.244859image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:32.273672image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:34.409117image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:36.228843image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:39.995109image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:41.627809image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:43.496691image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:46.334739image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:26.778236image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:31.033032image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:33.157071image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:35.085924image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:37.254864image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:40.640748image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:42.340631image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:44.263733image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:46.448951image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:27.168514image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:31.143542image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:33.265762image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:35.182125image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:37.524723image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:40.843699image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:42.451449image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:44.467254image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:46.545363image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:27.543434image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:31.248419image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:33.367678image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:35.271698image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:37.791182image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:40.940214image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:42.567381image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:44.556120image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:46.636236image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:27.911104image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:31.345383image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:33.463445image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:35.365273image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:38.044926image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:41.032803image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:42.661472image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:44.650099image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:47.146472image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:28.703350image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:31.866322image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:33.999261image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:35.845643image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:38.729710image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:41.222952image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:43.115416image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:45.189422image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:47.245127image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:29.110184image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:31.962271image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:34.096005image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:35.946932image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:38.911435image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:41.334100image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:43.215143image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:45.277980image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:47.344389image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:29.452891image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:32.076947image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:34.192183image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:36.041035image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:39.224492image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:41.447627image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:43.309599image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:45.376325image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:47.433895image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:29.866300image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:32.178483image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:34.286378image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:36.135282image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:39.703651image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:41.535773image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:43.401027image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:19:45.465674image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-05-09T21:19:53.721403image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-05-09T21:19:53.868251image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-05-09T21:19:54.019066image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-05-09T21:19:54.175006image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-05-09T21:19:54.498035image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-05-09T21:19:47.629889image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-05-09T21:19:48.460401image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-05-09T21:19:48.653725image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-05-09T21:19:48.779386image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
02179614https://www.tvmaze.com/episodes/2179614/kontakty-1x31-kontakty-v-telefone-eldara-dzarahova-morgenshtern-slava-marlow-basta-dana-poperecnyjКОНТАКТЫ в телефоне Эльдара Джарахова: Morgenshtern, Slava Marlow, Баста, Даня Поперечный1.031.0regular2020-12-2312:002020-12-23T00:00:00+00:0036.0nan49630https://www.tvmaze.com/shows/49630/kontaktyКонтактыGame ShowRussian[]Running30.041.02019-04-03nanhttps://www.youtube.com/playlist?list=PLZ1FUdedsrSJubWkFFh5vKHzawzQk1mYI53.0nannan1.651688e+09https://api.tvmaze.com/episodes/1977902
11988015https://www.tvmaze.com/episodes/1988015/muzskaa-tema-1x04-seria-4Серия 41.04.0regular2020-12-2312:002020-12-23T00:00:00+00:0030.0nan52520https://www.tvmaze.com/shows/52520/muzskaa-temaМужская темаTalk ShowRussian[]Ended30.030.02020-12-172020-12-25https://www.ivi.ru/watch/muzhskaya-tema3.0nan<p><b>Мужская тема</b> is a symbiosis of talk shows and modern podcasts, where male celebrities answer questions that concern people in the XXI century. Bright representatives of show business, theater, pop, cinema, sports, as well as Internet stars meet in the barbershop. Here, on male territory, they can openly discuss a variety of topics, sometimes seriously, and sometimes with humor. This is a chance to see the idol in a confidential communication without notes, compare his opinion with your own and hear what men really talk about when there is not a single girl around.</p>1.616723e+09https://api.tvmaze.com/episodes/2015818
22095629https://www.tvmaze.com/episodes/2095629/yi-nian-yong-heng-1x22-episode-22Episode 221.022.0regular2020-12-2310:002020-12-23T02:00:00+00:0019.0nan49652https://www.tvmaze.com/shows/49652/yi-nian-yong-hengYi Nian Yong HengAnimationChinese['Comedy', 'Action', 'Anime', 'Fantasy']Running19.019.02020-08-12nanhttps://v.qq.com/detail/w/ww18u675tfmhas6.html17.0nan<p>One will to create oceans. One will to summon the mulberry fields.<br /><br />One will to slaughter countless devils. One will to eradicate innumerable immortals.<br /><br />Only my will… is eternal.<br /><br />A Will Eternal tells the tale of Bai Xiaochun, an endearing but exasperating young man who is driven primarily by his fear of death and desire to live forever, but who deeply values friendship and family.<br /><br />(Source: Novel Updates)</p>1.649494e+09https://api.tvmaze.com/episodes/1964000
31993657https://www.tvmaze.com/episodes/1993657/7-days-of-romance-2x02-episode-2Episode 22.02.0regular2020-12-23nan2020-12-23T03:00:00+00:0015.0nan44276https://www.tvmaze.com/shows/44276/7-days-of-romance7 Days of RomanceScriptedKorean['Drama', 'Romance']EndedNaN15.02019-10-082021-01-20nan82.0nan<p>Da Eun works part-time and Kim Byul is an idol in her 5th years since debut. These two girls who look alike decide to change each other's lives just for 7 days. It tells the romantic encounters of these 2 girls.</p>1.650034e+09https://api.tvmaze.com/episodes/1995405
42015712https://www.tvmaze.com/episodes/2015712/half-fifty-1x01-episode-1Episode 11.01.0regular2020-12-23nan2020-12-23T03:00:00+00:0017.0nan53101https://www.tvmaze.com/shows/53101/half-fiftyHalf-FiftyScriptedKorean['Drama', 'Comedy']Ended17.017.02020-12-232020-12-23nan19.0nan<p><b>Half-Fifty</b> is a comedy drama about youth and growth, and the series follows a group of 25-year-olds who end up in the world of YouTubers.</p>1.611509e+09https://api.tvmaze.com/episodes/2007760
52015713https://www.tvmaze.com/episodes/2015713/half-fifty-1x02-episode-2Episode 21.02.0regular2020-12-23nan2020-12-23T03:00:00+00:0017.0nan53101https://www.tvmaze.com/shows/53101/half-fiftyHalf-FiftyScriptedKorean['Drama', 'Comedy']Ended17.017.02020-12-232020-12-23nan19.0nan<p><b>Half-Fifty</b> is a comedy drama about youth and growth, and the series follows a group of 25-year-olds who end up in the world of YouTubers.</p>1.611509e+09https://api.tvmaze.com/episodes/1985789
62015714https://www.tvmaze.com/episodes/2015714/half-fifty-1x03-episode-3Episode 31.03.0regular2020-12-23nan2020-12-23T03:00:00+00:0017.0nan53101https://www.tvmaze.com/shows/53101/half-fiftyHalf-FiftyScriptedKorean['Drama', 'Comedy']Ended17.017.02020-12-232020-12-23nan19.0nan<p><b>Half-Fifty</b> is a comedy drama about youth and growth, and the series follows a group of 25-year-olds who end up in the world of YouTubers.</p>1.611509e+09https://api.tvmaze.com/episodes/2039622
72015715https://www.tvmaze.com/episodes/2015715/half-fifty-1x04-episode-4Episode 41.04.0regular2020-12-23nan2020-12-23T03:00:00+00:0017.0nan53101https://www.tvmaze.com/shows/53101/half-fiftyHalf-FiftyScriptedKorean['Drama', 'Comedy']Ended17.017.02020-12-232020-12-23nan19.0nan<p><b>Half-Fifty</b> is a comedy drama about youth and growth, and the series follows a group of 25-year-olds who end up in the world of YouTubers.</p>1.611509e+09https://api.tvmaze.com/episodes/2039623
82015716https://www.tvmaze.com/episodes/2015716/half-fifty-1x05-episode-5Episode 51.05.0regular2020-12-23nan2020-12-23T03:00:00+00:0017.0nan53101https://www.tvmaze.com/shows/53101/half-fiftyHalf-FiftyScriptedKorean['Drama', 'Comedy']Ended17.017.02020-12-232020-12-23nan19.0nan<p><b>Half-Fifty</b> is a comedy drama about youth and growth, and the series follows a group of 25-year-olds who end up in the world of YouTubers.</p>1.611509e+09https://api.tvmaze.com/episodes/2324427
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Last rows

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771992698https://www.tvmaze.com/episodes/1992698/fightlore-1x06-the-pride-of-sakurabaThe Pride of Sakuraba1.06.0regular2020-12-23nan2020-12-23T17:00:00+00:0022.0<p>In the glory days of Japan's over-the-top MMA events, Kazushi Sakuraba embodied the samurai spirit of PRIDE Fighting Championship. Athletes, personalities and "The Gracie Hunter" himself tell how a pro wrestler became a superstar in the PRIDE ring.</p>48237https://www.tvmaze.com/shows/48237/fightloreFightLoreVarietyEnglish['Comedy', 'Sports']Running25.025.02020-04-18nanhttps://ufcfightpass.com/home70.0nan<p>A series focused on untold stories across UFC.</p>1.648443e+09https://api.tvmaze.com/episodes/1949336
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831990502https://www.tvmaze.com/episodes/1990502/king-gary-s01-special-christmas-specialChristmas Special1.0NaNsignificant_special2020-12-2322:002020-12-23T22:00:00+00:0035.0<p>In this festive special, Gray is looking forward to the Butterchurn Crescent Christmas lights display, which he hopes will brighten up the end of a difficult year - only for the event to be cancelled due to expense. Having landed a lucrative new contract at work, he takes it upon himself to save the lights - and Christmas.</p>45487https://www.tvmaze.com/shows/45487/king-garyKing GaryScriptedEnglish['Comedy']Running30.030.02020-01-10nanhttps://www.bbc.co.uk/programmes/p07w768676.0nan<p><b>King Gary</b> follows Gary King and love-of-his life, Terri as they bowl through family-life in suburbia. Gary's quest to impress the neighbours and fill dad, Big Gary's big shoes, might be more successful if he wasn't such a drama-queen but there's always a lot of love around in Butterchurn Crescent.</p>1.638563e+09https://api.tvmaze.com/episodes/1950703
841958868https://www.tvmaze.com/episodes/1958868/wwe-nxt-14x52-main-event-adam-cole-vs-velveteen-dreamMain Event: Adam Cole vs. Velveteen Dream14.052.0regular2020-12-2320:002020-12-24T01:00:00+00:00126.0nan2266https://www.tvmaze.com/shows/2266/wwe-nxtWWE NXTSportsEnglish[]Running120.075.02010-02-23nanhttp://www.wwe.com/inside/networkschedule88.0nan<p>Each Wednesday at 8:00 p.m. ET, WWE Superstars and Divas of tomorrow face off on <b>WWE NXT</b><i>,</i> a one-hour weekly show that features the brightest and best of WWE's rising stars. WWE NXT showcases the Superstars and Divas from WWE's Performance Center as well as appearances from WWE Superstars and Legends in an intimate setting. WWE NXT broadcasts from the state-of-the-art Full Sail LIVE venue on the Full Sail University in campus in Orlando, Florida.</p>1.651646e+09https://api.tvmaze.com/episodes/2050241
851945147https://www.tvmaze.com/episodes/1945147/noblesse-1x12-that-all-may-be-as-it-should-be-executionThat All May Be as It Should Be / Execution1.012.0regular2020-12-2300:002020-12-24T05:00:00+00:0025.0<p>As Raizel heads towards the sanctuary, his path is blocked by a powerful enemy. Meanwhile, Seira, who had been imprisoned, tries to escape to prevent Gejutel's being forced into eternal sleep. In order to protect Seira and Gejutel, Raizel and the others have to fight their own fierce battles. Can they save Seira and Gejutel?</p>49732https://www.tvmaze.com/shows/49732/noblesseNoblesseAnimationJapanese['Anime', 'Supernatural']Ended25.025.02015-12-042020-12-30https://noblesse-anime.com/44.0nan<p>Raizel awakens from his 820-year slumber. He holds the special title of Noblesse, a pure-blooded Noble and protector of all other Nobles. In an attempt to protect Raizel, his servant Frankenstein enrolls him at Ye Ran High School, where Raizel learns the simple and quotidian routines of the human world through his classmates. However, the Union, a secret society plotting to take over the world, dispatches modified humans and gradually encroaches on Raizel's life, causing him to wield his mighty power to protect those around him... After 820 years of intrigue, the secrets behind his slumber are finally revealed, and Raizel's absolute protection as the Noblesse begins!</p>1.648717e+09https://api.tvmaze.com/episodes/1970536